A SOFTWARE TOOL FOR QUALITY MEASUREMENT OF BUSINESS PROCESS MODELS USING DISTANCES IN N-DIMENSIONAL SPACE

Abstract

This paper considers the problem of quality measurement of business process models using the n-dimensional space distances. Business process models are graphical schemes similar to flowcharts or activity diagrams utilized in software engineering, usually represented using the BPMN (Business Process Model and Notation) or EPC (Event-driven Process Chain) notations. Business process modeling aims to capture current enterprise workflows for their analysis and then improvement using automation through IT (Information Technology) systems deployment. Therefore, designed business process models should be of high quality, so all “weak spots” of described organizational workflows could be properly identified and replaced with more efficient solutions. Whereas process models, which are not understandable, un-structured, and/or uncertain, may cause even more issues when used to improve organizational activities. Therefore, this study proposes quality measures and a software tool that can be used to detect errors in BPMN and EPC business process models using distances in n-dimensional space. The formal problem statement based on the graph-based description of business process models was given. Business process model quality characteristics and measures that consider features of both BPMN and EPC notations were proposed. Distances in n-dimensional space were suggested for usage to measure the quality of business process models. The algorithm for business process model quality measurement was proposed. The software tool to measure the quality of BPMN and EPC business process models was designed and developed. The quality of sample business process models was measured using the software tool. Obtained results were analyzed and discussed. This paper considers the Euclidean distance only, while other existing n-dimensional space distance measures or, on the opposite, similarity measures, can be used to evaluate business process model quality in further research.